如何轻松地将值分组以改善热图可视化

每个范围内来自熊猫组的pd.cut。它可以用来创建一个新的列'AgeGroup'用作pd.crosstab的输入。pd.cut的标签参数可以设置适当的文本作为y标记。right = False会照顾到等于垃圾箱边界的年龄，并将它们放在较高的垃圾箱中。一些示例代码：

import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns

df = pd.read_csv('http://www.ishelp.info/data/bikebuyers_original.csv')
df.rename(columns={"Purchased Bike": "purch_bike"}, inplace=True)

# bins = list(range(0, 80, 10)) + [120]
bins = [20, 28, 35, 42, 49, 56, 63, 70, 77, 84, 91, 120]
labels = [f'{a0}-{a1 - 1}' for a0, a1 in zip(bins[:-2], bins[1:-1])] + [f'≥{bins[-2]}']
df['AgeGroup'] = pd.cut(df.Age, bins=bins, labels=labels, right=False)

sns.heatmap(pd.crosstab(df.AgeGroup, df.purch_bike), annot=True, fmt='d')
plt.yticks(rotation=0)
plt.show()

回答来源：stackoverflow